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How to Practice Science (2025/2026: Semester 2 – Spring)
Cursusdoel
After completing this course students are able to:
- understand the similarities and differences of often used methods in science research.
- understand the interplay between a research question, the design and conclusions of a science research project.
- apply the basics of programming in Python to describe and organise data.
- understand the importance of scientific integrity, responsible data collection, and purpose of keeping a lab journal or logbook when doing research.
- present their research in different forms.
| Description of assignment | Assesses which learning goals? |
| Midterm exam Portfolio including lab journal, homework, and reflections Project reports including presentations Participation and professional attitude |
1, 3 2, 4 2, 5 - |
Vakinhoudelijk
Scientists attempt to answer a great variety of questions in their research. For this they need to decide on the best matching research design and set of methods. In this course, students learn when to use which type of method, and how that influences the research process and conclusions. The course focuses on three methods often used in empirical research across science disciplines: 1) simulation and modulation, 2) experimental, and 3) observational. Although there are many similarities between the methods (e.g. they all generate data, that can be analysed and from which conclusions can be drawn), there are important differences in their research design and application, determining the outcome. As such, this course teaches the basics of developing experimental, analytical, and research competences that are required to conduct research in any field within the sciences.
Students are first introduced to the empirical research cycle, focusing on turning a research question into a suitable design as it influences the choice of methods and type of data generated in science research. A small experiment will be conducted to show this interplay. By conducting the experiment, students also learn about two essential basic skills, that is recording all the steps in a lab journal, and programming (in Python). Students are also introduced to the principles of scientific integrity and how that plays a role in research design (e.g. lab and ethical skills, handling and storing data).
To apply and deepen the knowledge and skills, students then do a practical project based on simulation/modulation or laboratory work, followed by an observational project using a database to answer a research question. In the first project, the focus is on collecting data on a given research question and associated design, either in a laboratory or using computer simulations and modelling. The second project focuses on analysing and visualising data depending on different research questions from a given database. Students experience how the different methods are typically applied in science research and learn skills connected to these methods. In doing so, students experience which approach matches their interest most and are prepared for doing scientific research in the lab courses.
Format
Lectures, interactive sessions, and homework
Practical projects
Target audience for the pilot in Spring 2026
This Science course is open to all second and first year students, no matter their major. Any leftover places are available to third year students.
Students are first introduced to the empirical research cycle, focusing on turning a research question into a suitable design as it influences the choice of methods and type of data generated in science research. A small experiment will be conducted to show this interplay. By conducting the experiment, students also learn about two essential basic skills, that is recording all the steps in a lab journal, and programming (in Python). Students are also introduced to the principles of scientific integrity and how that plays a role in research design (e.g. lab and ethical skills, handling and storing data).
To apply and deepen the knowledge and skills, students then do a practical project based on simulation/modulation or laboratory work, followed by an observational project using a database to answer a research question. In the first project, the focus is on collecting data on a given research question and associated design, either in a laboratory or using computer simulations and modelling. The second project focuses on analysing and visualising data depending on different research questions from a given database. Students experience how the different methods are typically applied in science research and learn skills connected to these methods. In doing so, students experience which approach matches their interest most and are prepared for doing scientific research in the lab courses.
Format
Lectures, interactive sessions, and homework
Practical projects
Target audience for the pilot in Spring 2026
This Science course is open to all second and first year students, no matter their major. Any leftover places are available to third year students.
Though this course can be used as a preparation for level 2 lab modules, it does not fulfill any methodology requirement at this moment. You can also do this course if you have already completed lab courses.
Werkvormen
UCU course
Toetsing
participation and professional attitude
Verplicht | Weging 10% | ECTS 0,75
Portfolio including lab journal, homework, and reflections
Verplicht | Weging 20% | ECTS 1,5
Project reports including presentations
Verplicht | Weging 40% | ECTS 3
*midterm FEEDBACK*
Niet verplicht
Midterm exam
Verplicht | Weging 30% | ECTS 2,25
Ingangseisen en voorkennis
Ingangseisen
Er is geen informatie over verplichte ingangseisen bekend.
Voorkennis
UCACCACA11 and at least one Science course are recommended. This course itself may also count as the SCI breadth requirement though.
Voertalen
- Engels
Competenties
-
Academisch schrijven
-
Interdisciplinariteit
-
Onderzoeksvaardigheden
-
Presenteren
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Samenwerken
Cursusmomenten
Gerelateerde studies
Tentamens
Er is geen tentamenrooster beschikbaar voor deze cursus
Verplicht materiaal
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BOEKPeter K. Dunn (2021). Scientific Research and Methodology: An introduction to quantitative research in science and health. https://bookdown.org/pkaldunn/Book (open access)
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BOEKChapters from Gopal, R., Philps, D., & Weyde, T. (2023). Foundations of Programming, Statistics, and Machine Learning for Business Analytics. SAGE Publications, Ltd. (UK). https://bookshelf.vitalsource.com/books/9781529621563
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DIVERSE- Reader for learning Python programming - Readers for the projects - open access Python software - open access databases
Aanbevolen materiaal
Er is geen informatie over de aanbevolen literatuur bekend
Opmerkingen
Counts as SCI breadth requirement
Coördinator
| dr. G.S.A.T. van Rossum | G.S.A.T.vanRossum@uu.nl |
Docenten
| dr. G.E.N. Mojet | g.e.n.mojet@uu.nl |
| T. van Gils MSc | t.vangils@uu.nl |
| dr. G.S.A.T. van Rossum | G.S.A.T.vanRossum@uu.nl |
| dr. G.M. Terra-Bleeker | G.M.Terra@uu.nl |
Inschrijving
Let op: deze cursus is niet toegankelijk voor studenten van andere faculteiten, bijvakkers mogen zich dus niet inschrijven.
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